Evidence map›Paper›PMID 36434939›Full record

ArticleClinical imaging2023

Can a chest HRCT-based crash course on COVID-19 cases make inexperienced thoracic radiologists readily available to face the next pandemic?

Lorenzo Cereser, Emanuele Passarotti, Annarita Tullio, Vincenzo Patruno, Leonardo Monterubbiano, Pierpaolo Apa, Chiara Zuiani, Rossano Girometti

Open access · greenAbstract read
In one paragraph

Article in Clinical imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 82% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Lorenzo CereserInstitute of Radiology, Department of Medicine, University of Udine, University Hospital "S. Maria della Misericordia", p.le S. Maria della Misericordia, 15, 33100 Udine, Italy. Electronic address: lcereser@sirm.org.
Emanuele PassarottiInstitute of Radiology, Department of Medicine, University of Udine, University Hospital "S. Maria della Misericordia", p.le S. Maria della Misericordia, 15, 33100 Udine, Italy.
Annarita TullioInstitute of Hygiene and Clinical Epidemiology, University Hospital "S. Maria della Misericordia", p.le S. Maria della Misericordia, 15, 33100 Udine, Italy.
Vincenzo PatrunoPulmonology Department, "S. Maria della Misericordia" University Hospital, p.le S. Maria della Misericordia, 15, 33100 Udine, Italy. Electronic address: vincenzo.patruno@asufc.sanita.fvg.it.
Leonardo MonterubbianoInstitute of Radiology, Department of Medicine, University of Udine, University Hospital "S. Maria della Misericordia", p.le S. Maria della Misericordia, 15, 33100 Udine, Italy.
Pierpaolo ApaInstitute of Radiology, Department of Medicine, University of Udine, University Hospital "S. Maria della Misericordia", p.le S. Maria della Misericordia, 15, 33100 Udine, Italy.
Chiara ZuianiInstitute of Radiology, Department of Medicine, University of Udine, University Hospital "S. Maria della Misericordia", p.le S. Maria della Misericordia, 15, 33100 Udine, Italy. Electronic address: chiara.zuiani@uniud.it.
Rossano GiromettiInstitute of Radiology, Department of Medicine, University of Udine, University Hospital "S. Maria della Misericordia", p.le S. Maria della Misericordia, 15, 33100 Udine, Italy. Electronic address: rgirometti@sirm.org.
University of Udine · ITOspedale Santa Maria della Misericordia di Udine · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo test the inter-reader agreement in assessing lung disease extent, HRCT signs, and Radiological Society of North America (RSNA) categorization between a chest-devoted radiologist (CR) and two HRCT-naïve radiology residents (RR1 and RR2) after the latter attended a COVID-19-based chest high-resolution computed tomography (HRCT) "crash course".

methodsThe course was built by retrospective inclusion of 150 patients who underwent HRCT for COVID-19 pneumonia between November 2020 and January 2021. During a first 10-days-long "training phase", RR1 and RR2 read a pool of 100/150 HRCTs, receiving day-by-day access to CR reports as feedback. In the subsequent 2-days-long "test phase", they were asked to report 50/150 HRCTs with no feedback. Test phase reports of RR1/RR2 were then compared with CR using unweighted or linearly-weighted Cohen's kappa (k) statistic and intraclass correlation coefficient (ICC).

resultsWe observed almost perfect agreement in assessing disease extent between RR1-CR (k = 0.83, p < 0.001) and RR2-CR (k = 0.88, p < 0.001). The agreement between RR1-CR and RR2-CR on consolidation, crazy paving pattern, organizing pneumonia (OP) pattern, and pulmonary artery (PA) diameter was substantial (k = 0.65 and k = 0.68), moderate (k = 0.42 and k = 0.51), slight (k = 0.10 and k = 0.20), and good-to-excellent (ICC = 0.87 and ICC = 0.91), respectively. The agreement in providing RSNA categorization was moderate for R1 versus CR (k = 0.56) and substantial for R2 versus CR (k = 0.67).

conclusionHRCT-naïve readers showed an acceptable overall agreement with CR, supporting the hypothesis that a crash course can be a tool to readily make non-subspecialty radiologists available to cooperate in reading high burden of HRCT examinations during a pandemic/epidemic.

Indexed as

COVID-19Lung Diseases, InterstitialHumansLungPandemicsRadiologistsRetrospective StudiesCOVID-19EducationPandemicsRadiologists

Identifiers

PMID36434939
PMCPMC9678839
OpenAlexW4309726415

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.